UNIVERSIDADE FEDERAL DE MINAS GERAIS INSTITUTO DE CIÊNCIAS BIOLÓGICAS DEPARTAMENTO DE BIOLOGIA GERAL PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA PhD Thesis In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile PhD candidate: Mariana Passos Santana Thesis supervisor: Anderson Miyoshi Thesis co-supervisor: Sandeep Tiwari BELO HORIZONTE July 2019 MARIANA PASSOS SANTANA In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile Thesis presented as partial requirement for the degree of Doctor in Genetics, to the Department of General Biology at the Institute of Biological Sciences, Federal University of Minas Gerais. SUPERVISOR: Prof. Dr. Anderson Miyoshi CO-SUPERVISOR: Dr. Sandeep Tiwari BELO HORIZONTE July 2019 ii 043 Santana, Mariana Passos. In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile [manuscrito] / Mariana Passos Santana. – 2019. 225 f. : il. ; 29,5 cm. Orientador: Prof. Dr. Anderson Miyoshi. Co-orientador: Dr. Sandeep Tiwari. Tese (doutorado) – Universidade Federal de Minas Gerais, Instituto de Ciências Biológicas. Programa de Pós-Graduação em Genética. 1. Genômica. 2. Imunização. 3. Vacinologia. 4. Corynebacterium diphtheriae. 5. Clostridium difficile. 6. Resistência a Múltiplos Medicamentos. I. Miyoshi, Anderson. II. Tiwari, Sandeep. III. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. IV. Título. CDU: 575 Ficha elaborada pela Biblioteca do Instituto de Ciências Biológias da UFMG Ficha elaborada pela Biblioteca do Instituto de Ciências Biológias da UFMG Ficha catalográfica elaborada pela Biblioteca do Instituto de Ciências Biológicas da UFMG “Na vida, não existe nada a temer, mas a entender” Marie Curie “Quem elegeu a busca Não pode recusar a travessia” Guimarães Rosa iv ACKNOWLEDGEMENTS Firstly, I would like to express my sincere gratitude to my advisors Prof. Dr. Anderson Miyoshi and Dr. Sandeep Tiwari for the continuous support of my Ph.D study and related research, for their patience, motivation, and immense knowledge. The guidance helped me in all the time of research and writing of this thesis. I could not have imagined having better advisors for my Ph.D study. Besides my advisors, I would like to thank the rest of my thesis committee: Prof. Dr. Álvaro Cantini, Prof. Dr. Rommel Ramos, Prof. Dr. Sergio Costa Oliveira, and Prof. Dr. Siomar de Castro Soares, for their insightful comments and encouragement, but also for the hard questions that incented me to widen my research from various perspectives. My thanks also goes to Prof. Dr. Vasco Azevedo, Dr. Pascale Serror, and Dr. Francis Repoila, who provided me an opportunity to join their team, and who gave access to the laboratory and research facilities. A very special gratitude goes out to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for providing my scholarship and funding during my PhD. I thank my fellow labmates from TecnoGen, LGCM and CPE (especially Stephane, Kato, Tati and Vanessa) for the stimulating discussions and friendship; it was great sharing laboratory with all of you during the last years. In addition, I thank my friends from UFMG and INRA. Last but not the least, I would like to thank my family: my parents (Rita e Alfredo), my sister (Andreia), brothers (Alfredo e Rick) and nephew (Lucca) for their continuous support, love and patience, you bring light to my life. To my aunts, uncles, cousins, and friends (Gatas, Chicas, amigos de BH, Viçosa e Paris) for supporting me spiritually throughout writing this thesis. Thank you all for everything; I love you! Thanks for all your encouragement! v SUMARY ABREVIATION................................................................................................................................................. ix LIST OF FIGURES ........................................................................................................................................... x LIST OF TABLES ............................................................................................................................................ xii ABSTRACT ..................................................................................................................................................... xiii INTRODUCTION ........................................................................................................................................... 14 1. The human microbiota and related diseases ....................................................................................... 15 2. The interplay between microbiota, pathogens and immune system ................................................... 18 2.1. Innate immune response ............................................................................................................... 22 2.2. Adaptive immune response .......................................................................................................... 23 3. Vaccines ................................................................................................................................................ 27 3.1. Classical vaccination classification ............................................................................................... 31 3.1.1. Live attenuated vaccines ........................................................................................................... 32 3.1.2. Killed or inactivated vaccines ................................................................................................... 33 3.1.3. Subunit and Conjugate Vaccines .............................................................................................. 33 3.1.4. Inactivated toxin (toxoids) ........................................................................................................ 34 3.2. Vaccine adjuvant and delivery system ......................................................................................... 34 3.3. Next-generated vaccines ............................................................................................................... 37 3.3.1. Next-generation vaccines and OMICs approach ..................................................................... 38 3.3.2. Next-generated vaccines methodologies ................................................................................... 41 3.3.2.1. Reverse vaccinology .............................................................................................................. 41 3.3.2.2. Immunoinformatics .............................................................................................................. 42 3.3.2.3. Structural vaccinology .......................................................................................................... 42 vi 4. The two sides of antibiotic treatment and possible alternatives .......................................................... 42 CHAPTER I: Design of a broad-spectrum candidate multi-epitope vaccine against Diphtheria: An integrative immunoinformatics approach ....................................................................................................... 45 1. Corynebacterium diphtheriae: a life-threating bacteria ....................................................................... 46 1.1. The Corynebacterium genus .......................................................................................................... 46 1.2. The pathogenic bacteria C. diphtheriae ........................................................................................ 47 1.3. C. diphtheriae factors associated with infection ........................................................................... 50 1.3.1. Diphtheria toxin and the diphtheria toxin repressor ............................................................... 52 1.3.2. DIP0733 ..................................................................................................................................... 54 1.3.3. Pili proteins ............................................................................................................................... 55 2. Diphtheria............................................................................................................................................. 56 2.1. Main characteristics, transmission and clinical manifestations .................................................. 56 2.2. Diagnosis and treatment ............................................................................................................... 58 2.3. Diphtheria vaccine ........................................................................................................................ 59 2.4. Application of cutting-edge approaches to improve diphtheria management ............................ 62 3. Submitted paper: Design of a broad-spectrum candidate multi-epitope vaccine against Diphtheria: An integrative immunoinformatics approach ................................................................................................. 63 Supplementary Tables - Design of a broad-spectrum candidate multi-epitope vaccine against Diphtheria: An interagive immunoinformatics approach..........................................................................................................